Research on wind farm participating in AGC based on wind power variogram characteristics

Area of Science:

• Electrical Engineering
• Power Systems
• Renewable Energy Integration

Background:

• Large-scale wind power integration complicates maintaining power system frequency stability.
• Conventional generators face increased pressure for frequency regulation, necessitating wind farm participation.
• System frequency deviations become more difficult to manage with rising wind power penetration.

Purpose of the Study:

• To develop a coordinated control strategy for wind farms to participate in automatic generation control (AGC).
• To enhance the frequency stability of interconnected power systems with significant wind power integration.
• To ensure conventional units and wind farms work together effectively in AGC.

Main Methods:

• Established a multi-area interconnected power system frequency response model incorporating wind power.
• Presented the state-space model of the regional interconnected power system.
• Introduced wind power variogram characteristics for estimating wind power variations across different time scales.
• Developed a wind farm participation strategy in AGC using model predictive control (MPC) based on predicted wind power variations.

Main Results:

• The proposed model accurately represents the frequency response of interconnected power systems with wind power.
• Wind power variations were effectively estimated using variogram characteristics.
• The MPC-based control strategy enabled coordinated participation of conventional units and wind farms in AGC.
• Simulation results demonstrated the feasibility and validity of the proposed coordinated control strategy.

Conclusions:

• The developed strategy effectively manages frequency deviations in power systems with high wind power penetration.
• Coordinated control of wind farms and conventional units is crucial for grid stability.
• Model predictive control offers a viable approach for integrating wind power into AGC systems.